[pabs3]

Are there similar things for other types of GPUs?

Edit: the site has one project per GPU type, shame there isn't one interface that works with every GPU type instead.

[eigenspace]

https://github.com/JuliaGPU/AMDGPU.jl

https://github.com/JuliaGPU/oneAPI.jl

These are both less mature than CUDA.jl, but are in active development.

> Edit: the site has one project per GPU type, shame there isn't one interface that works with every GPU type instead.

That would be https://juliagpu.github.io/KernelAbstractions.jl

[pabs3]

https://github.com/JuliaGPU/KernelAbstractions.jl

[jpsamaroo]

For kernel programming, https://github.com/JuliaGPU/KernelAbstractions.jl (shortened to KA) is what the JuliaGPU team has been developing as a unified programming interface for GPUs of any flavor. It's not significantly different from the (basically identical) interfaces exposed by CUDA.jl and AMDGPU.jl, so it's easy to transition to. I think the event system in KA is also far superior to CUDA's native synchronization system, since it allows one to easily express graphs of dependencies between kernels and data transfers.

[krastanov]

These libraries provide the same API, so from a user perspective, as long as you do not need low-level access, it does not matter what your GPU is.

However, the low-level library for AMD GPUs is more of an alpha quality in Julia.